Policy transformation techniques in policy-based systems management

Beigi, Mandis; Calo, Seraphin; Verma, Dinesh

doi:10.1109/policy.2004.1309146

Cited by 50 publications

(36 citation statements)

References 7 publications

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“…One type of approach is to use machine learning techniques to support policy refinement. Verma [8] proposes a case-based reasoning approach to support policy refinement. In this approach the system learns experimentally from the operational behaviour it has previously examined.…”

Section: Discussionmentioning

confidence: 99%

Realising Adaptive Web Services through Automated Policy Refinement

Carey

Wade

2007

2007 10th IFIP/IEEE International Symposium on Integrated Network Management

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Abstract-Traditionally policy based management systems have relied on 'engineered' policy refinement to decompose high level policies down to low level policies for implementation 111121. Such management systems typically rely on a policy designer ensuring that a high level policy creates the necessary invocations or events to trigger the correct low level policies (and their implementation). The difficulty with this approach is that human error in the policy design can lead to feature interaction problems, conflicts and errors 131, 141. This refinement problem is a key challenge for policy based management to be adopted widely within service management (voted #1 key challenge at Policy 2005 panel session).In this paper we concentrate on policy based management of web services, where the web services have adaptive behaviors. The paper proposes the design, implementation and evaluation of a suite of policy development tools which (i) facilitate the specification of adaptive web services (which are to be managed by a policy based system) using finite state machines to describe the permitted adaptive behaviors, (ii) supports the specification of supportable (functionally correct) high level management policies, the automated refinement of these high level policies and the auto-generation of enforceable (low level) policies. The paper also presents an evaluation of the systems with particular reference to the usability of the proposed solution. The paper also provides a brief presentation of related research in policy refinement and distinguishes the proposed approach from published work. Finally the paper concludes by drawing initial findings and identifies future work.

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Section: Discussionmentioning

confidence: 99%

Realising Adaptive Web Services through Automated Policy Refinement

Carey

Wade

2007

2007 10th IFIP/IEEE International Symposium on Integrated Network Management

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“…The main limitation of this approach is the absence of any analysis capabilities to evaluate the consistency of the refined policies. Similarly, work presented in [19] allows the translation of service-level objectives into configuration parameters of a managed system. The transformation engine takes the service requirements of the user as input, and searches the database to determine the optimal parameter values that provide a required level of service.…”

Section: Related Workmentioning

confidence: 99%

Towards policy refinement for resilience management in cloud

Shirazi

Simpson

Syeda

et al. 2016

2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM)

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Abstract-Cloud computing is becoming increasingly important for provision of critical services because of potential cost saving, scalability and elasticity. Therefore, it is particularly important for clouds and cloud-based services to be resilient, i.e., they are able to operate correctly and continuously even in the presence of challenges. To do this, a number of resiliencesupporting mechanisms are needed at various levels in cloud infrastructure. It is non-trivial to manage these mechanisms and there is a need for flexible instruments which assist cloud providers in this complex task. Policy based management is an established instrument to manage resilience supporting mechanisms and they are useful if it allows not only high level description of abstract policy (e.g high level security and resilience requirements), but also enables such policy to be refined and eventually mapped into an appropriate low levels in cloud settings. This paper sheds light on basic concepts behind policy based management in cloud, more specifically it emphasizes the use of policy refinement which is the process of translating higher level requirements (such as security and resilience requirements) into the sequence of actions at lower levels that can implement them, in order to generate more refined policies that govern the behaviour of an overall cloud system when under challenge. We finally present two example scenarios on how policy refinement can work for the cloud to establish its relevance for the overall resilience management.

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“…To date an automated domain-independent goal decomposition mechanism has not emerged. A case-based reasoning approach is proposed in [6] to assist the refinement process based on the clustering of goals in previous refinements, but requires a large training set of previous refinement operations. A semi-manual approach for addictively reasoning over available sub-goals into super-goals is suggested in [3], but this system only operates on previously refined sub-goals.…”

Section: Policy Decomposition and Refinementmentioning

confidence: 99%